Mrs. Mehri Aghdamigargari | Mining Engineering | Best Researcher Award
Mrs. Mehri Aghdamigargari, University of Arizona, United States
mehri aghdamigargari is currently a Ph.D. student in Mining Engineering at the University of Arizona, Tucson, United States, where she focuses on sustainable mine production planning. Her research is centered on multi-objective approaches that maximize net present value (NPV) while minimizing social impacts, such as blasting vibrations. She has a strong academic background in industrial engineering and mathematics, with advanced expertise in optimization, statistical modeling, and data analysis.
PROFILE
Educational Details
Ph.D. in Mining Engineering
University of Arizona, Tucson, United States
GPA: 3.66/4
Thesis: “Sustainable Mine Production Planning: A Multi-Objective Approach for Maximizing NPV and Minimizing Social Impacts of Blasting Vibration”
Relevant Courses: Surface Mine Planning & Design, Optimization Methods, Data Analysis, Engineering Statistics
Dates: August 2023 – Present
Master of Science in Industrial Engineering – Economic and Social Systems
Bu-Ali Sina University, Hamedan, Iran
GPA: 17.05/20
Thesis: “Comparison Between the Performance of IMOLP and DNN Methods by Simulating Decision Maker’s Behavior and Proposing a Compound Method” (Grade: 19/20)
Dates: September 2007 – September 2010
Bachelor of Science in Industrial Engineering
Payame Noor University, Tabriz, Iran
GPA: 16.32/20
Final Project: “Using Simulation to Model Six Sigma Indices in Complex Processes with Variable Throughput Probability” (Grade: 20/20)
Dates: September 2015 – September 2017
Bachelor of Science in Mathematics – Teaching
Shahid Rajaee Teacher Training University, Tehran, Iran
GPA: 16.05/20
Dates: September 2002 – June 2006
Professional Experience
mehri aghdamigargari has a diverse professional background spanning research, teaching, and academic leadership. From January 2020 to August 2023, she served as a Research Assistant at Nazarbayev University in Nur-Sultan, Kazakhstan. In this role, she spearheaded various optimization projects aimed at enhancing industrial efficiency and reducing waste. Her work involved detailed data analysis and root cause investigation, which she skillfully communicated through comprehensive reports, presentations, and scientific publications—contributing to innovation in industrial systems and process reliability.
Prior to her research role, mehri spent over a decade teaching mathematics and statistics at the high school level in Tabriz, Iran, from September 2006 to January 2020. Her dedication to education helped students build strong foundations in quantitative subjects, preparing them for advanced studies and careers in STEM fields.
Additionally, from September 2011 to September 2016, mehri held a position as a Master & Lecturer at Payame Noor University in Jolfa, Iran, where she taught courses in statistics, operations research, and computer programming within the industrial engineering department. Her role not only involved teaching but also mentoring students in applied engineering practices, further honing her ability to convey complex concepts effectively. Through these experiences, mehri has developed a versatile skill set that integrates academic research, teaching, and industry applications, making her a valuable contributor to both educational and professional fields.
mehri aghdamigargari’s research interests encompass a range of advanced analytical techniques and methodologies, including operations research, optimization, statistical and computational modeling, and data analysis with a focus on machine learning. Her work in operations research allows her to apply mathematical and analytical methods to make better decisions and solve complex problems in industries such as mining and manufacturing. Her expertise in optimization involves developing and implementing methods to improve efficiency and productivity, often balancing multiple objectives to maximize benefits while minimizing costs or environmental impacts.
In the field of statistical and computational modeling, mehri uses quantitative models to represent real-world processes, providing valuable insights into system behavior and enabling predictive analytics. Additionally, her skills in data analysis and machine learning allow her to process and analyze large datasets to uncover patterns and relationships, driving data-driven decision-making. Her combined expertise across these areas positions her at the forefront of research aimed at improving industrial systems through rigorous, data-informed approaches.
Awards, and Honors
Metallurgical Inputs to Integrated Planning Short Course – April 2024
Mine Engineering Inputs to Integrated Planning Short Course – October 2023
Data Analysis with Python – July 2024
Modeling and Optimization with Python – April 2024
Deep Learning Course – January 2023
Python Comprehensive Course – January 2022
Becoming a Student Assistant: Teaching and Mentoring – November 2022
Leadership Role: Head of Mathematics Department Student Science Group, Shahid Rajaee Teacher Training University (Sep 2004 – Jun 2006)
Editorial Membership: Mathematics Scientific Magazine Editorial Team (Sep 2004 – Jun 2006)
National Mathematics Olympics: Second Rank, City-Level – April 2000
A hybrid mathematical modelling approach for energy generation from hazardous waste during the COVID-19 pandemic
Authors: J. Valizadeh, M. Aghdamigargari, A. Jamali, U. Aickelin, S. Mohammadi, et al.
Journal: Journal of Cleaner Production
Year: 2021
Volume: 315
Article Number: 128157
DOI: 10.1016/j.jclepro.2021.128157
Sustainability in Long-term Surface Mine Planning: A Systematic Review of Operations Research Applications
Authors: M. Aghdamigargari, S. Avane, A. Anani, S. O. Adewuyi
Journal: Sustainability
Year: 2024
Volume: 16(22)
Article Number: 9769
DOI: 10.3390/su16229769
Predicting the cumulative variation of 3-D mechanical assemblies using an ‘Idea Algebra’ framework
Authors: M. Aghdamigargari, C. Spitas
Journal: Journal of Engineering Design
Year: 2022
Volume: 33(6)
Pages: 441-460
DOI: 10.1080/09544828.2022.2070057
Two new hybrid algorithms for solving multi-objective linear programming problems
Authors: M. Aghdamigargari, A. Kheirkhah
Conference: 4th International Conference on Operation Research
Year: 2011
A hybrid algorithm using interior-point methods and neural networks for solving multi-objective linear programming problems
Authors: M. Aghdamigargari, A. Kheirkhah
Conference: International Conference on Operation Research
Year: 2010
In conclusion, Mrs. Mehri Aghdamigargari is a highly qualified candidate for the Best Researcher Award. Her exceptional academic background, diverse professional experience, and active engagement in research and technological advancements in the fields of industrial optimization and sustainability make her a standout candidate. Additionally, her technical expertise and teaching experience further highlight her contributions to the field of engineering. Therefore, she is highly deserving of this recognition for her ongoing commitment to excellence in research.